1. Finish the discussion on transformation
2. Introduction to classification problem:
2.1. Bayesian setting, density estimation.
2.2. Normal case -linear discriminant analysis
2.3. Nearest neighbor
2.4. Classification trees.
2.5. Neural net work.
2.6. Support vector machine.
2.7. Bootstrapping.
2.8. Others.